Artificial intelligence (AI) is very quickly expanding in the healthcare industry. AI’s primary role has been to automate processes to make it easier for employees to work on more complex people-related concerns. Yet as the technology develops, Healthcare Central reports that AI is also being used as a diagnostic tool. With a faster, more accurate way of detecting illnesses, and administering treatments, the mortality rate could be significantly reduced. This includes the treatment of conditions like cancer.
Tag: Deep Learning
Wild Data Part 3: Transfer Learning
Did you know that the word “hippopotamus” is a word of Greek origin? Hippos- comes from “horse” and -potamos means “river”. The funny thing here would be to imagine when Greeks run into this animal for the very first time. There was not a word for every single animal around the world, so they probably thought something like “what a strange horse…!!! Maybe the river has something to do with it. Got it! It will be a hippo-potamus!”
Wild Data Part 2: Transfer Style
This is the second post of our Wild Data series. In this post, we are going to expose how to transfer style from one image to another. Here, the most interesting point is to know that we won’t use a neural network to classify a set of classes as usual. I mean, we don’t need to train a network for a specific approach. Transfer style is based on pre-trained networks such as it could be a VGG19 trained with ImageNet (one million of images). Thus, a good understanding of transfer style will help you to better understand how convolutional neural networks works for vision. Let’s go on!
Wild Data Part 1: Augmentation
Let’s imagine that you want to buy a new car, and you fall in love with this new car’s brand. Because you really want that car, the car’s brand comes out everywhere in your daily life, even though the amount of these cars remain the same. Our brain is trained to focus on what it wants to see.
Introduction to Deep Learning Part 2: Parameters and Configuration
In the first session of our Deep Learning series, we described the basis of our approach to Deep Learning: the classical theory of neural networks. In this second we will try to focus on more practical aspects, such as the use of hyperparameters.
Introduction to Deep Learning Part 1: Neural Networks
The processes to train a machine are not that different from those that take place when humans learn. Indeed, scientists took inspiration from the human brain to create neural networks: When we try to make a complex concept understandable, an immediate/natural way is to try and remember the way we originally absorbed the concept, what made us understand it or what we used to make it easier.